Principal Data Engineer

Career Category

Information Systems

Role Description:

Let’s do this. Let’s change the world. We are looking for highly motivated expert Principal Data Engineer who can own the design & development of complex data pipelines, solutions and frameworks for R&D domain. The ideal candidate will be responsible to design, develop, and optimize data pipelines, data integration frameworks, and metadata-driven architectures that enable seamless data access and analytics. This role prefers deep expertise in big data processing, distributed computing, data modeling, and governance frameworks to support self-service analytics, AI-driven insights, and enterprise-wide data management.

Roles & Responsibilities:

- Architect and maintain robust, scalable data pipelines using Databricks, Spark, and Delta Lake, enabling efficient batch and real-time processing.

- Lead efforts to evaluate, adopt, and integrate emerging technologies and tools that enhance productivity, scalability, and data delivery capabilities.

- Drive performance optimization efforts, including Spark tuning, resource utilization, job scheduling, and query improvements.

- Identify and implement innovative solutions that streamline data ingestion, transformation, lineage tracking, and platform observability.

- Build frameworks for metadata-driven data engineering, enabling reusability and consistency across pipelines.

- Foster a culture of technical excellence, experimentation, and continuous improvement within the data engineering team.

- Collaborate with platform, architecture, analytics, and governance teams to align platform enhancements with enterprise data strategy.

- Define and uphold SLOs, monitoring standards, and data quality KPIs for production pipelines and infrastructure.

- Partner with cross-functional teams to translate business needs into scalable, governed data products.

- Mentor engineers across the team, promoting knowledge sharing and adoption of modern engineering patterns and tools.

- Collaborate with cross-functional teams, including data architects, business analysts, and DevOps teams, to align data engineering strategies with enterprise goals.